On Calibration of Modern Neural Networks

14 June 2017

Papers citing "On Calibration of Modern Neural Networks"

50 / 1,060 papers shown

Title
Supermasks in Superposition Mitchell Wortsman Vivek Ramanujan Rosanne Liu Aniruddha Kembhavi Mohammad Rastegari J. Yosinski Ali Farhadi SSL CLL 22 279 0 26 Jun 2020
Gradient-EM Bayesian Meta-learning Yayi Zou Xiaoqi Lu BDL 25 16 0 21 Jun 2020
Estimating Model Uncertainty of Neural Networks in Sparse Information Form Jongseo Lee Matthias Humt Jianxiang Feng Rudolph Triebel BDL UQCV 38 46 0 20 Jun 2020
Calibration of Model Uncertainty for Dropout Variational Inference M. Laves Sontje Ihler Karl-Philipp Kortmann T. Ortmaier BDL UQCV 32 18 0 20 Jun 2020
Evaluating Prediction-Time Batch Normalization for Robustness under Covariate Shift Zachary Nado Shreyas Padhy D. Sculley Alexander DÁmour Balaji Lakshminarayanan Jasper Snoek OOD AI4TS 30 238 0 19 Jun 2020
Distribution-free binary classification: prediction sets, confidence intervals and calibration Chirag Gupta A. Podkopaev Aaditya Ramdas UQCV 27 79 0 18 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 8 57 0 18 Jun 2020
LiDARsim: Realistic LiDAR Simulation by Leveraging the Real World S. Manivasagam Shenlong Wang K. Wong Wenyuan Zeng Mikita Sazanovich Shuhan Tan Binh Yang Wei-Chiu Ma R. Urtasun 3DPC 8 221 0 16 Jun 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts Bertrand Charpentier Daniel Zügner Stephan Günnemann UQCV UD EDL BDL 25 169 0 16 Jun 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 35 11 0 16 Jun 2020
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift Sheheryar Zaidi Arber Zela T. Elsken Chris Holmes Frank Hutter Yee Whye Teh OOD UQCV 18 71 0 15 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 14 7 0 15 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 22 9 0 12 Jun 2020
The Curious Case of Convex Neural Networks S. Sivaprasad Ankur Singh Naresh Manwani Vineet Gandhi 46 26 0 09 Jun 2020
Self-Distillation as Instance-Specific Label Smoothing Zhilu Zhang M. Sabuncu 12 115 0 09 Jun 2020
An Empirical Analysis of the Impact of Data Augmentation on Knowledge Distillation Deepan Das Haley Massa Abhimanyu Kulkarni Theodoros Rekatsinas 21 18 0 06 Jun 2020
AI Research Considerations for Human Existential Safety (ARCHES) Andrew Critch David M. Krueger 22 50 0 30 May 2020
Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes Sebastian W. Ober Laurence Aitchison BDL 26 60 0 17 May 2020
Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models Jayaraman J. Thiagarajan Bindya Venkatesh Rushil Anirudh P. Bremer J. Gaffney G. Anderson B. Spears 8 21 0 05 May 2020
On the Inference Calibration of Neural Machine Translation Shuo Wang Zhaopeng Tu Shuming Shi Yang Liu 19 80 0 03 May 2020
Physarum Powered Differentiable Linear Programming Layers and Applications Zihang Meng Sathya Ravi Vikas Singh 21 5 0 30 Apr 2020
The Right Tool for the Job: Matching Model and Instance Complexities Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith 33 167 0 16 Apr 2020
Calibrating Structured Output Predictors for Natural Language Processing Abhyuday N. Jagannatha Hong-ye Yu 20 28 0 09 Apr 2020
LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood Abhinav Kumar Tim K. Marks Wenxuan Mou Ye Wang Michael J. Jones A. Cherian T. Koike-Akino Xiaoming Liu Chen Feng CVBM 3DV 17 150 0 06 Apr 2020
Self-Augmentation: Generalizing Deep Networks to Unseen Classes for Few-Shot Learning Jinhwan Seo Hong G Jung Seong-Whan Lee SSL 12 39 0 01 Apr 2020
Regularizing Class-wise Predictions via Self-knowledge Distillation Sukmin Yun Jongjin Park Kimin Lee Jinwoo Shin 27 274 0 31 Mar 2020
Hybrid Classification and Reasoning for Image-based Constraint Solving Maxime Mulamba Jayanta Mandi Rocsildes Canoy Tias Guns 33 11 0 24 Mar 2020
On Calibration of Mixup Training for Deep Neural Networks Juan Maroñas D. Ramos-Castro Roberto Paredes Palacios UQCV 25 6 0 22 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 98 0 20 Mar 2020
MINT: Deep Network Compression via Mutual Information-based Neuron Trimming Madan Ravi Ganesh Jason J. Corso S. Y. Sekeh MQ 35 15 0 18 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
A Unified View of Label Shift Estimation Saurabh Garg Yifan Wu Sivaraman Balakrishnan Zachary Chase Lipton 16 139 0 17 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 21 220 0 16 Mar 2020
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods Sanghyuk Chun Seong Joon Oh Sangdoo Yun Dongyoon Han Junsuk Choe Y. Yoo AAML OOD 329 53 0 09 Mar 2020
PAC-Bayes meta-learning with implicit task-specific posteriors Cuong C. Nguyen Thanh-Toan Do G. Carneiro BDL 36 7 0 05 Mar 2020
Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation Sangdon Park Osbert Bastani James Weimer Insup Lee 23 52 0 29 Feb 2020
Towards Universal Representation Learning for Deep Face Recognition Yichun Shi Xiang Yu Kihyuk Sohn Manmohan Chandraker Anil K. Jain CVBM OOD 17 148 0 26 Feb 2020
Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data Yen-Chang Hsu Yilin Shen Hongxia Jin Z. Kira OODD 24 558 0 26 Feb 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 33 277 0 24 Feb 2020
Real-Time Detectors for Digital and Physical Adversarial Inputs to Perception Systems Y. Kantaros Taylor J. Carpenter Kaustubh Sridhar Yahan Yang Insup Lee James Weimer AAML 14 12 0 23 Feb 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip H. S. Torr P. Dokania UQCV 56 444 0 21 Feb 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation Dmitry Molchanov Alexander Lyzhov Yuliya Molchanova Arsenii Ashukha Dmitry Vetrov TPM 17 84 0 21 Feb 2020
Spatiotemporal Relationship Reasoning for Pedestrian Intent Prediction Bingbin Liu Ehsan Adeli Zhangjie Cao Kuan-Hui Lee Abhijeet Shenoi Adrien Gaidon Juan Carlos Niebles 23 150 0 20 Feb 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 24 639 0 20 Feb 2020
Being Bayesian about Categorical Probability Taejong Joo U. Chung Minji Seo UQCV BDL 25 58 0 19 Feb 2020
A Financial Service Chatbot based on Deep Bidirectional Transformers S. Yu Yuxin Chen Hussain Zaidi 17 33 0 17 Feb 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 27 482 0 17 Feb 2020
Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning Arsenii Ashukha Alexander Lyzhov Dmitry Molchanov Dmitry Vetrov UQCV FedML 33 314 0 15 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 19 115 0 13 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 14 89 0 11 Feb 2020